Thippa Reddy Gadekallu – författare

Computer vision is an interdisciplinary scientific field that deals with how computers obtain, store, interpret and understand digital images or videos using artificial intelligence based on neural networks, machine learning and deep learning methodologies. They are used in countless applications such as image retrieval and classification, driving and transport monitoring, medical diagnostics and aerial monitoring.Written by a team of international experts, this edited book covers the state-of-the-art of advanced research in the fields of computer vision and recognition systems from fundamental concepts to methodologies and technologies and real world applications including object detection, biometrics, Deepfake detection, sentiment and emotion analysis, traffic enforcement camera monitoring, vehicle control and aerial remote sensing imagery.The book will be useful for industry and academic researchers, scientists and engineers in the fields of computer vision, machine vision, image processing and recognition, multimedia, AI, machine and deep learning, data science, biometrics, security, and signal processing. It will also make a great course reference for advanced students and lecturers in these fields of research.

Industry 5.0 is the upcoming industrial revolution where people will be working together with smart machines and robots, thereby bringing human touch and intelligence back to the decision-making process. Challenges include the security and privacy of sensitive multimedia data and near zero latency for mission critical applications.Federated learning is a machine learning technique that trains algorithms across multiple decentralized edge devices or servers by holding local data samples without exchanging them. This approach stands in contrast to traditional centralized machine learning techniques where all local datasets are uploaded to one server. This method enables multiple actors to build a common, robust machine learning model without sharing data, thus addressing critical issues such as data privacy, data security, data access rights and access to heterogeneous data.The objective of this book is to show how federated learning can solve multimedia data processing and security challenges in Industry 5.0. The book introduces new research paradigms for the security and privacy preservation of multimedia data. It provides a detailed discussion on how federated learning can be used to handle big data, preserve privacy, reduce computational and communication costs; and shows how to integrate federated learning with other disruptive technologies including blockchain, digital twins and 5G and beyond.Federated Learning for Multimedia Data Processing and Security in Industry 5.0 is an essential reference for advanced students, lecturers, and academic and industry researchers working in the fields of machine learning federated learning, computer and network security, data science, multimedia, computer vision and Industry 5.0 applications.

This book offers a selection of the best papers presented at the International scientific conference “Digital Transformation in Industry: Trends, Management, Strategies”, held by the Institute of Economics of the Ural Branch of the Russian Academy of Sciences (Ekaterinburg, Russia) on December 16–17, 2024.Focusing on the practical implementation of artificial intelligence and digital technologies in industrial settings, the book explores cutting-edge solutions for managing digital transformation across sectors and regions. The chapters cover a wide range of topics, including AI-based sustainable industrial practices, lean-based digital integration, intelligent logistics and digital supply chain innovations, cloud-edge data architectures, the organization of cyber-physical systems, and scientific and technological development.Emphasizing both theoretical frameworks and real-world implementation, the book is essential for scientists, industry professionals, policymakers, and researchers seeking to understand and leverage AI and digital technologies for strategic advancement and competitive advantage.

This book offers a selection of the best papers presented at the International scientific conference “Digital Transformation in Industry: Trends, Management, Strategies”, held by the Institute of Economics of the Ural Branch of the Russian Academy of Sciences (Ekaterinburg, Russia) on December 16–17, 2024.Focusing on the practical implementation of artificial intelligence and digital technologies in industrial settings, the book explores cutting-edge solutions for managing digital transformation across sectors and regions. The chapters cover a wide range of topics, including AI-based sustainable industrial practices, lean-based digital integration, intelligent logistics and digital supply chain innovations, cloud-edge data architectures, the organization of cyber-physical systems, and scientific and technological development.Emphasizing both theoretical frameworks and real-world implementation, the book is essential for scientists, industry professionals, policymakers, and researchers seeking to understand and leverage AI and digital technologies for strategic advancement and competitive advantage.

This book brings together selected papers presented at the International Scientific Conference “Digital Transformation in Industry: Trends, Management, Strategies” (DTI), held in Ekaterinburg, Russia, on November 19–21, 2025, as part of the biennial DTI framework. Organized by the Institute of Economics of the Ural Branch of the Russian Academy of Sciences, the conference further developed the strategic research agenda initiated at DTI-2024, with particular emphasis on the theme ‘Artificial Intellect in Industry: Effects, Barriers, and the Directions of National Policy’. The book is structured around five interconnected thematic areas. First, it addresses applied cases of artificial intelligence and emerging trajectories of industrial development, including comparative national experiences, sectoral applications, human–machine interaction on the shopfloor, and AI-enabled energy and sustainability solutions. Second, it explores the optimization of business processes and business models through digitalization, focusing on data management, organizational change, and the transformation of enterprise decision-making. Third, it considers digital ecosystem architectures and platform-based solutions, highlighting agent-based modeling, adaptive identification methods, cross-border innovation platforms, hardware emulation tools, and regional dimensions of digital transformation. Fourth, the volume examines the human dimension of AI adoption, including human-centered manufacturing, education, employment, digital skills, wages, and human capital formation under Industry 5.0. Finally, the book explores the application of AI-driven tools in FinTech and cybersecurity, with chapters addressing large language models and proactive cyberattack detection. Taken together, the chapters offer theoretical, methodological, and empirical perspectives on the restructuring of industrial systems under the influence of AI. The book will be of interest to scholars, practitioners, and policymakers engaged in the study and implementation of AI-driven industrial transformation.

The book “Applied Assistive Technologies and Informatics for Students with Disabilities” provides a comprehensive guide to assist students with learning disabilities in higher education via modern assistive technologies and informatics. This book will take us on a tour of the various modern assistive technologies, such as artificial intelligence (AI), blockchain, computer vision (CV), text analytics (TA), the metaverse, human-computer interaction (HCI), digital twins (DT), and federated learning (FL), and how they support higher education students with learning disabilities.This book is intended for students with learning disabilities, scientists and researchers, lecturers and teachers, academic and corporate libraries, practitioners, and professionals who are interested in providing inclusive education to students with learning disabilities through the application of modern assistive technologies and informatics. This book is ideal for readers who are new to the subject and knowledgeable about the principles of inclusive education. In addition, it is a fantastic resource for teachers and parents assisting students with learning disabilities. This book can be a powerful tool to educate more students about learning disabilities, which can help eradicate the bullying of these students.

The book “Applied Assistive Technologies and Informatics for Students with Disabilities” provides a comprehensive guide to assist students with learning disabilities in higher education via modern assistive technologies and informatics. This book will take us on a tour of the various modern assistive technologies, such as artificial intelligence (AI), blockchain, computer vision (CV), text analytics (TA), the metaverse, human-computer interaction (HCI), digital twins (DT), and federated learning (FL), and how they support higher education students with learning disabilities.

This book is intended for students with learning disabilities, scientists and researchers, lecturers and teachers, academic and corporate libraries, practitioners, and professionals who are interested in providing inclusive education to students with learning disabilities through the application of modern assistive technologies and informatics. This book is ideal for readers who are new to the subject and knowledgeable about the principles of inclusive education. In addition, it is a fantastic resource for teachers and parents assisting students with learning disabilities. This book can be a powerful tool to educate more students about learning disabilities, which can help eradicate the bullying of these students.